Relevant bibliographies by topics / Mathematical modeling

Academic literature on the topic 'Mathematical modeling'

Author: Grafiati
Published: 4 June 2021
Last updated: 27 July 2024

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Journal articles on the topic "Mathematical modeling"

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Mitra, Novelyn L., Ma Jobelle R. David, and Rommel Pariñas Deus Gleena P. Pascual. "Predictive Modeling for Criminology Licensure Examination Success Through Mathematical Modelling." International Journal of Research Publication and Reviews 5, no. 3 (March 2, 2024): 168–76. http://dx.doi.org/10.55248/gengpi.5.0324.0604.

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Guha, Probal, and Vaishnavi Unde. "Mathematical Modeling of Spiral Heat Exchanger." International Journal of Engineering Research 3, no. 4 (April 1, 2014): 226–29. http://dx.doi.org/10.17950/ijer/v3s4/409.

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Latysheva, O., and Yu Chupryna. "Economic and Mathematical Modeling in Budgeting." Economic Herald of the Donbas, no. 4 (74) (2023): 32–36. http://dx.doi.org/10.12958/1817-3772-2023-4(74)-32-36.

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The article is devoted to an overview of modern modeling approaches for effective management of enterprise budgets. The article examines the toolkit of economic and mathematical modeling that can be used in the budgeting system. It is proposed to increase the efficiency of the budgeting process by applying the tools of economic and mathematical modeling at the stages of budget development and resource allocation, as well as in the process of budget control and monitoring. To increase the clarity of the simulation procedure and results, a visualization of the TO BE model is presented in IDF0 notation (simulation language) on the Ramus platform. It is noted that the effectiveness of the budgeting system based on the use of economic-mathematical modeling tools will allow to improve resource expenditure planning taking into account the opportunities, priorities, needs and limitations of a specific enterprise and its external business environment. The need to implement digitalization tools and economic-mathematical modeling in the budgeting system is substantiated. The purpose of the article is to analyze the possibilities of forming an effective enterprise budgeting system based on the successful implementation of economic and mathematical modeling tools. The authors focus on the potential of using business analytics as a result of using economic and mathematical modeling tools to form an effective budgeting system. The article argues for the possibility of effectively using modeling tools in the budgeting process, which allows enterprises to make high-quality management decisions based on forecasts, scenarios, optimization recommendations, visualization of current problem situations, etc. The scientific novelty of this article lies in the fact that the recommendations and conclusions provided by the authors can be useful for domestic enterprises in the current conditions of severe restrictions on available resources, lack of free funds, existing and potential risks. In general, this article is useful for those who want to learn more about the possibilities of using economic-mathematical modeling tools in the budgeting system.
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Longo, R. T. "Mathematical modeling technique." AIP Advances 9, no. 12 (December 1, 2019): 125211. http://dx.doi.org/10.1063/1.5129638.

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Gerstenschlager, Natasha E., and Katherine Ariemma Marin. "GPS: Mathematical Modeling." Mathematics Teacher: Learning and Teaching PK-12 115, no. 9 (September 2022): 668–73. http://dx.doi.org/10.5951/mtlt.2022.0128.

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Growing Problem Solvers provides four original, related, classroom-ready mathematical tasks, one for each grade band. Together, these tasks illustrate the trajectory of learners’ growth as problem solvers across their years of school mathematics.
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Zarubin, V. S., and E. S. Sergeeva. "Mathematical modeling of structural-sensitive nanocomposites deformation." Computational Mathematics and Information Technologies 2, no. 1 (2018): 17–24. http://dx.doi.org/10.23947/2587-8999-2018-2-1-17-24.

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VASHISHTHA, PUSHPENDRA KUMAR, ROHIT GOEL, PRIYANKA SAHNI, and ASHWINI KUMAR. "A Mathematical Modeling of University Examination System." Paripex - Indian Journal Of Research 3, no. 5 (January 15, 2012): 174–76. http://dx.doi.org/10.15373/22501991/may2014/53.

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Klyuchko, O. M. "SOME TRENDS IN MATHEMATICAL MODELING FOR BIOTECHNOLOGY." Biotechnologia Acta 11, no. 1 (February 2018): 39–57. http://dx.doi.org/10.15407/biotech11.01.039.

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Haris, Denny. "USING VIRTUAL LEARNING ENVIRONMENT ON REALISTIC MATHEMATICS EDUCATION TO ENHANCE SEVENTH GRADERS’ MATHEMATICAL MODELING ABILITY." SCHOOL EDUCATION JOURNAL PGSD FIP UNIMED 12, no. 2 (June 28, 2022): 152–59. http://dx.doi.org/10.24114/sejpgsd.v12i2.35387.

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Many research studied that realistic mathematics education (RME) can be an alternative solution to students’ difficulties in learning mathematics. Various forms of technology additionally are further employed to support students' mathematical achievements. However, research on the implementation of virtual learning environments (VLE) with the RME approach is still lacking. The main goals of this research were to create an instructional process of virtual learning environments on realistic mathematics education to improve seventh graders' mathematical modeling abilities and to examine the effect of designs on mathematical modeling ability. Theory of realistic mathematics education and virtual learning environment literature were integrated. The design model developed was verified by experts to be tested. The pre-test / post-test test method was carried out to see the effectiveness of the design. The sixty-seventh graders from a secondary school in North Sumatera were selected as samples. The instructional process developed consists of four stages, namely (1) purposing contextual problems, (2) defining situations from contextual problems, (3) solving problems individually or in groups, and (4) reviewing and comparing solutions. The developed virtual learning environment consists of 5 components, namely (1) users management, (2) content and activities management, (3) resources management, (4) visualization and communication management, and (5) evaluation and assessment management. The mathematical modeling ability concerning experimental group students is significantly higher after being taught through a realistic mathematics education instructional process via a virtual learning environment. Comparison of the experimental group with the control group also showed the same results.
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Hwang, Seonyoung, and Sunyoung Han. "A Study on Mathematical Modeling Trends in Korea." Korean Society of Educational Studies in Mathematics - Journal of Educational Research in Mathematics 33, no. 3 (August 31, 2023): 639–66. http://dx.doi.org/10.29275/jerm.2023.33.3.639.

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Mathematical modeling refers to a core competency and teaching-learning method that is being treated as important worldwide. This study aimed at examining trends of previous studies on mathematical modeling, which were published in Korean journals. This study was conducted with the aim of introducing domestic studies on mathematical modeling to both domestic and foreign researchers. Fifty-four studies from 2013 to 2022 were selected for the current trend study and classified in terms of years, research subjects, and research methods. By year, at least one paper and up to 10 papers were published from 2013 to 2022. As a result of examining the trends of the studies by subject, we revealed that studies targeting teachers were very insufficient. Moreover, the findings show that biased research methods and quantitatively simple analysis methods were mainly used. Last, the relational trend between research topics and implications were diverse depending on the theme such as task, lesson, and teacher education. Specifically, although the studies have provided implications on teacher education steadily, research targeting the topic of teacher education for mathematical modeling have been very limited. For the future study on mathematical modeling, mathematics educators and researchers need to recognize that teacher education is significant in implementing mathematical modeling in school classrooms successively, and to try diverse studies on teacher education for mathematical modeling. This paper will contribute to helping foreign scholars to know the research on mathematical modeling being conducted in Korea, which will ultimately contribute to the literature on mathematical modeling.
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Dissertations / Theses on the topic "Mathematical modeling"

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Beauchamp, Robert Edward. "Mathematical modeling using Maple." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1996. http://handle.dtic.mil/100.2/ADA319951.

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Phillips, Donovan D. "Mathematical modeling using MATLAB." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1998. http://handle.dtic.mil/100.2/ADA358796.

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Thesis (M.S. in Applied Mathematics) Naval Postgraduate School, December 1998.
"December 1998." Thesis advisor(s): Maurice D. Weir. Includes bibliographical references (p. 121). Also available online.
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Green, Terrell J. "Mathematical modeling of fire /." The Ohio State University, 1987. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487331541710161.

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Pillutla, R. R. "Mathematical modeling of biosystems." Thesis(Ph.D.), CSIR-National Chemical Laboratory, Pune, 1991. http://dspace.ncl.res.in:8080/xmlui/handle/20.500.12252/3013.

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Wilmer, Archie. "Javelin analysis using mathematical modeling." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA283466.

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Thesis (M.S. in Applied Mathematics) Naval Postgraduate School, June 1994.
Thesis advisor(s): Bard K. Mansager, Maurice D. Weir. "June 1994." Includes bibliographical references. Also available online.
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Pratikakis, Nikolaos. "Mathematical modeling of rail gun." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Sep%5FPratikakis.pdf.

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Thesis (M.S. in Mechanical Engineering)--Naval Postgraduate School, September 2006.
Thesis Advisor(s): Kwon Young. "September 2006." Includes bibliographical references (p. 77-78). Also available in print.
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Weens, William. "Mathematical modeling of liver tumor." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2012. http://tel.archives-ouvertes.fr/tel-00779177.

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Comme démontre récemment pour la régénération du foie après un dommage cause par intoxication, l'organisation et les processus de croissance peuvent être systématiquement analyses par un protocole d'expériences, d'analyse d'images et de modélisation [43]. Les auteurs de [43] ont quantitativement caractérise l'architecture des lobules du foie, l'unité fonctionnelle fondamentale qui constitue le foie, et en ont conçu un modèle mathématique capable de prévoir un mécanisme jusqu'alors inconnu de division ordonnée des cellules. La prédiction du modèle fut ensuite validée expérimentalement. Dans ce travail, nous étendons ce modèle a l'échelle de plusieurs lobules sur la base de résultats expérimentaux sur la carcinogène dans le foie [15]. Nous explorons les scénarios possibles pouvant expliquer les différents phénotypes de tumeurs observés dans la souris. Notre modèle représente les hépatocytes, principal type de cellule dans le foie, comme des unités individuels avec un modèle a base d'agents centré sur les cellules et le système vasculaire est représenté comme un réseau d'objets extensibles. L'équation de Langevin qui modélise le mouvement des objets est calculée par une discrétisation explicite. Les interactions mécaniques entre cellules sont modélisées avec la force de Hertz ou de JKR. Le modèle est paramètre avec des valeurs mesurables a l'échelle de la cellule ou du tissue et ses résultats sont directement comparés avec les résultats expérimentaux. Dans une première étape fondamentale, nous étudions si les voies de transduction du signal de Wnt et Ras peuvent expliquer les observations de [15] où une prolifération instantanée dans les souris mutées est observée seulement si 70% des hépatocytes sont dépourvues d'APC. Dans une deuxième étape, nous présentons une analyse de sensibilité du modèle sur la rigidité de la vasculature et nous la mettons en relation avec un phénotype de tumeur (observe expérimentalement) où les cellules tumorales sont bien différentiées. Nous intégrons ensuite dans une troisième 'étape la destruction de la vasculature par les cellules tumorales et nous la mettons en relation avec un autre phénotype observe expérimentalement caractérise par l'absence de vaisseaux sanguins. Enfin, dans la dernière étape de notre étude nous montrons que des effets qui sont détectables dans les petits nodules tumoraux et qui reflètent les propriétés des cellules tumorales, ne sont plus présents dans la forme ou dans le phénotype des tumeurs d'une taille excédant la moitié de celle d'un lobule.
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Blomqvist, Oscar, Sebastian Bremberg, and Richard Zauer. "Mathematical modeling of flocking behavior." Thesis, KTH, Optimeringslära och systemteori, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-103812.

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In this thesis, the ocking behaviour of prey when threatened by a group of predators, is investigated using dynamical systems. By implementing the unicycle model, a simulation is created using Simulink and Matlab. A set of forces are set up to describe the state of the prey, that in turn determines their behaviour in dierent scenarios. An eective strategy is found so all members of the ock can survive the predator attack, taking into account the advantages of the predator's greater translational velocity and the prey's higher angular velocity. Multiple obstacles and an energy constraint are added to make the model more realistic. The objective of this thesis is to develop a strategy that maximizes the chance of survival of each ock member by not only staying together in a group but also making use of environmental advantages.
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Keller, Peter. "Mathematical modeling of molecular motors." Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6304/.

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Amongst the many complex processes taking place in living cells, transport of cargoes across the cytosceleton is fundamental to cell viability and activity. To move cargoes between the different cell parts, cells employ Molecular Motors. The motors operate by transporting cargoes along the so-called cellular micro-tubules, namely rope-like structures that connect, for instance, the cell-nucleus and outer membrane. We introduce a new Markov Chain, the killed Quasi-Random-Walk, for such transport molecules and derive properties like the maximal run length and time. Furthermore we introduce permuted balance, which is a more flexible extension of the ordinary reversibility and introduce the notion of Time Duality, which compares certain passage times pathwise. We give a number of sufficient conditions for Time Duality based on the geometry of the transition graph. Both notions are closely related to properties of the killed Quasi-Random-Walk.
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Kleinstreuer, Nicole Churchill. "Mathematical modeling of renal autoregulation." Thesis, University of Canterbury. Bioengineering, 2009. http://hdl.handle.net/10092/2532.

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Renal autoregulation is unique and critically important in maintaining homeostasis in the body via control of renal blood flow and filtration. The myogenic reflex responds directly to pressure variation and is present throughout the vasculature in varying degrees, while the tubuloglomerular feedback (TGF) mechanism adjusts microvascular resistance and glomerular filtration rate (GFR) to maintain distal tubular NaCl delivery. No simple models are available which allow the independent contributions of the myogenic and TGF responses to be compared and which include control over multiple metabolic and physiological parameters. Independently developed mathematical models of myogenic autoregulation and TGF control of GFR have been combined to produce a comprehensive model for the rat kidney which is responsive to multiple small step changes in mean arterial pressure. The system encompasses every level of the renal vasculature and the tubular system of the nephrons while simultaneously incorporating the modulatory effects of changes in viscosity and shear stress-induced nitric oxide (NO) production. The vasculature of the rat kidney has previously been divided via a Strahler ordering scheme using morphological data derived from micro-CT imaging. This data, combined with an extensive literature review of the relevant experimental data, led to the development of order-specific parameter sets for each of the eleven vascular levels. The model of the myogenic response depends primarily on circumferential wall tension, corresponding to a distally dominant resistance distribution with the highest contributions localized to the afferent arterioles and interlobular arteries. The constrictive response is tempered by the vasodilatory influence of flow-induced NO. Experimental comparison with data from groups that inhibited the TGF mechanism showed that the model was able to accurately reproduce the characteristics of renal myogenic autoregulation. This myogenic model was coupled with a system of equations that represented both spatial and temporal changes in concentration of the filtrate in the tubular system of the nephrons and the corresponding resistance changes of the afferent arteriole via the TGF mechanism. Computer simulation results of the system response to pressure perturbations were examined, as well as the interaction between mechanisms and the modulatory influences of metabolic and hemodynamic factors on the steady state and transient characteristics of whole-organ renal autoregulation. The responses of the model were consistent with experimental observations and showed that the frequency of the myogenic reflex was approximately 0.4 Hz while that of TGF was 0.06 Hz, corresponding to a 2-3 sec response time for myogenic contraction and 16.7 sec for TGF. Within the autoregulatory range step increases in pressure induced damped oscillations in tubular flow, macula densa NaCl concentration, arteriolar diameter, and renal blood flow. The model demonstrated that these oscillations were triggered by TGF and confined to vessels less than 100 micrometer in diameter. The pressure response in larger vessels remained important in characterizing total autoregulatory efficacy. Examination of the steady-state and transient characteristics of the model results demonstrates the necessity of considering the whole organ response in studies of renal autoregulation. A comprehensive model of autoregulation also allows for the examination of pathological states, such as the altered NO production in hypertension or the excess tubular reabsorption of water seen in diabetes. The model was able to reproduce experimental results when simulating diseased states, enabling the analysis of impaired autoregulation as well as the identification of key factors affecting the autoregulatory response.
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Books on the topic "Mathematical modeling"

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McDuffie, Amy Roth, ed. Mathematical Modeling and Modeling Mathematics. Reston, VA: National Council of Teachers of Mathematics, 2016.

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Palacios, Antonio. Mathematical Modeling. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04729-9.

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Heinz, Stefan. Mathematical Modeling. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20311-4.

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Eck, Christof, Harald Garcke, and Peter Knabner. Mathematical Modeling. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55161-6.

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Uvarova, Ludmila A., and Anatolii V. Latyshev, eds. Mathematical Modeling. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3397-6.

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Mathematical modeling. Heidelberg: Springer, 2011.

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Meerschaert, Mark M. Mathematical modeling. 3rd ed. Burlington, MA: Elsevier Academic Press, 2007.

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Meerschaert, Mark M. Mathematical modeling. 2nd ed. San Diego, Calif: Academic Press, 1999.

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Phi Delta Kappa. Educational Foundation., ed. Mathematical modeling. Bloomington, Ind: Phi Delta Kappa Educational Foundation, 1995.

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Lesh, Richard, Peter L. Galbraith, Christopher R. Haines, and Andrew Hurford, eds. Modeling Students' Mathematical Modeling Competencies. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6271-8.

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Book chapters on the topic "Mathematical modeling"

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Mahlke, Debora. "Mathematical Modeling." In A Scenario Tree-Based Decomposition for Solving Multistage Stochastic Programs, 15–38. Wiesbaden: Vieweg+Teubner, 2011. http://dx.doi.org/10.1007/978-3-8348-9829-6_3.

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Hartt, Kenneth. "Mathematical Modeling." In Mathematical Tools for Physicists, 213–48. Weinheim, FRG: Wiley-VCH Verlag GmbH & Co. KGaA, 2006. http://dx.doi.org/10.1002/3527607773.ch8.

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Ganguli, Ranjan, Dipali Thakkar, and Sathyamangalam Ramanarayanan Viswamurthy. "Mathematical Modeling." In Smart Helicopter Rotors, 41–70. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24768-7_2.

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Helmig, Rainer. "Mathematical modeling." In Multiphase Flow and Transport Processes in the Subsurface, 85–140. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60763-9_3.

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Frenz, Christopher. "Mathematical Modeling." In Visual Basic and Visual Basic .NET for Scientists and Engineers, 271–84. Berkeley, CA: Apress, 2002. http://dx.doi.org/10.1007/978-1-4302-1139-6_13.

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Yang, Xin-She. "Mathematical Modeling." In Mathematical Modeling with Multidisciplinary Applications, 23–44. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118462706.ch2.

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Boukas, El-Kébir, and Fouad M. AL-Sunni. "Mathematical Modeling." In Mechatronic Systems, 47–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22324-2_3.

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Ledder, Glenn. "Mathematical Modeling." In Mathematics for the Life Sciences, 83–143. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7276-6_2.

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Moura Neto, Francisco Duarte, and Antônio José da Silva Neto. "Mathematical Modeling." In An Introduction to Inverse Problems with Applications, 7–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-32557-1_2.

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Radojčić, Dejan, Milan Kalajdžić, and Aleksandar Simić. "Mathematical Modeling." In Power Prediction Modeling of Conventional High-Speed Craft, 11–18. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30607-6_2.

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Conference papers on the topic "Mathematical modeling"

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Riyanto, Bambang. "Designing Mathematical Modeling Tasks for Learning Mathematics." In 2nd National Conference on Mathematics Education 2021 (NaCoME 2021). Paris, France: Atlantis Press, 2022. http://dx.doi.org/10.2991/assehr.k.220403.007.

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Riyanto, Bambang. "Designing Mathematical Modeling Tasks for Learning Mathematics." In 2nd National Conference on Mathematics Education 2021 (NaCoME 2021). Paris, France: Atlantis Press, 2022. http://dx.doi.org/10.2991/assehr.k.220403.007.

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Riyanto, Bambang. "Designing Mathematical Modeling Tasks for Learning Mathematics." In 2nd National Conference on Mathematics Education 2021 (NaCoME 2021). Paris, France: Atlantis Press, 2022. http://dx.doi.org/10.2991/assehr.k.220403.007.

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Xiaoyuan, Luo, and Liu Jun. "Review of Mathematical Modeling in Applied Mathematics Education." In 2013 Fourth International Conference on Intelligent Systems Design and Engineering Applications (ISDEA). IEEE, 2013. http://dx.doi.org/10.1109/isdea.2013.530.

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Ito, H. M. "Introduction to mathematical modeling of earthquakes." In Modeling complex systems. AIP, 2001. http://dx.doi.org/10.1063/1.1386820.

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Leite, Lourenildo W. B., Boris P. Sibiryakov, and Wildney W. S. Vieira. "Mathematical Modeling Anticline Reservoirs." In 14th International Congress of the Brazilian Geophysical Society & EXPOGEF, Rio de Janeiro, Brazil, 3-6 August 2015. Brazilian Geophysical Society, 2015. http://dx.doi.org/10.1190/sbgf2015-003.

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Andreotti, Luciano C., and Sérgio N. Vannucci. "Shock Absorber Mathematical Modeling." In SAE Brasil 98 VII International Mobility Technology Conference and Exhibit. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1998. http://dx.doi.org/10.4271/982959.

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Abgaryan, Karine. "MATHEMATICAL MODELING OF NEUROMORPHIC SYSTEM." In Mathematical modeling in materials science of electronic component. LLC MAKS Press, 2020. http://dx.doi.org/10.29003/m1518.mmmsec-2020/56-60.

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The paper deals with the creation of mathematical models for the development and optimization of the operation of neuromorphic systems. A multiscale approach based on set-theoretic representations is presented, which makes it possible to quickly develop software with a parallel computing mechanism for creating neuromorphic systems
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Sun, Jie, and Shanshan Wang. "Integration of Mathematical Modeling Thought and Main Courses of Mathematics." In CIPAE 2021: 2021 2nd International Conference on Computers, Information Processing and Advanced Education. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3456887.3457502.

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Meng, HuiFang, and Fangjian Fu. "The Infiltration of Mathematical Modeling Thought in Advanced Mathematics Teaching." In 2017 4th International Conference on Education, Management and Computing Technology (ICEMCT 2017). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/icemct-17.2017.114.

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Reports on the topic "Mathematical modeling"

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Mitler, Henri E. Mathematical modeling of enclosure fires. Gaithersburg, MD: National Institute of Standards and Technology, 1991. http://dx.doi.org/10.6028/nist.ir.90-4294.

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Rajagopal, K., M. Massoudi, and J. Ekmann. Mathematical modeling of fluid-solid mixtures. Office of Scientific and Technical Information (OSTI), March 1990. http://dx.doi.org/10.2172/7230272.

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Quiang, Ji. Mathematical modeling plasma transport in tokamaks. Office of Scientific and Technical Information (OSTI), January 1997. http://dx.doi.org/10.2172/565310.

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Mitler, Henri E., and John A. Rockett. How accurate is mathematical fire modeling? Gaithersburg, MD: National Bureau of Standards, 1986. http://dx.doi.org/10.6028/nbs.ir.86-3459.

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Jin, D., R. G. Stachowiak, I. V. Samarasekera, and J. K. Brimacombe. Mathematical modeling of deformation during hot rolling. Office of Scientific and Technical Information (OSTI), December 1994. http://dx.doi.org/10.2172/34420.

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Lerman, Kristina, Maja Mataric, and Aram Galstyan. Mathematical Modeling of Large Multi-Agent Systems. Fort Belvoir, VA: Defense Technical Information Center, September 2005. http://dx.doi.org/10.21236/ada439172.

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Rehm, Ronald G., and Randall J. McDermott. Mathematical modeling of wildland-urban interface fires. Gaithersburg, MD: National Institute of Standards and Technology, 2011. http://dx.doi.org/10.6028/nist.ir.7803.

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Bras, R. L., G. E. Tucker, and V. Teles. Six Myths About Mathematical Modeling in Geomorphology. Fort Belvoir, VA: Defense Technical Information Center, January 2003. http://dx.doi.org/10.21236/ada416086.

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Booth, Victoria, Daniel Forger, and Cecilia Diniz Behn. Mathematical Modeling of Circadian and Homeostatic Interaction. Fort Belvoir, VA: Defense Technical Information Center, November 2011. http://dx.doi.org/10.21236/ada563698.

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Aceves, Alejandro B. Mathematical Modeling of Novel Optical Fiber Devices. Fort Belvoir, VA: Defense Technical Information Center, December 1997. http://dx.doi.org/10.21236/ada342522.

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